2 resultados para COSMIC RAY DETECTION
em Repositório Científico da Universidade de Évora - Portugal
Resumo:
The signature of 60Fe in deep-sea crusts indicates that one or more supernovae exploded in the solar neighbourhood about 2.2 million years ago1–4. Recent isotopic analysis is consistent with a core-collapse or electron-capture supernova that occurred 60 to 130 parsecs from the Sun5. Moreover, peculiarities in the cosmic ray spectrum point to a nearby supernova about two million years ago6. The Local Bubble of hot, diffuse plasma, in which the Solar System is embedded, originated from 14 to 20 supernovae within a moving group, whose surviving members are now in the Scorpius– Centaurus stellar association7,8. Here we report calculations of the most probable trajectories and masses of the supernova progenitors, and hence their explosion times and sites. The 60Fe signal arises from two supernovae at distances between 90 and 100 parsecs. The closest occurred 2.3 million years ago at present-day galactic coordinates l = 327°, b = 11°, and the second-closest exploded about 1.5 million years ago at l = 343°, b = 25°, with masses of 9.2 and 8.8 times the solar mass, respectively. The remaining supernovae, which formed the Local Bubble, contribute to a smaller extent because they happened at larger distances and longer ago (60Fe has a half- life of 2.6 million years9,10). There are uncertainties relating to the nucleosynthesis yields and the loss of 60Fe during transport, but they do not influence the relative distribution of 60Fe in the crust layers, and therefore our model reproduces the measured relative abundances very well.
Resumo:
Knee osteoarthritis is the most common type of arthritis and a major cause of impaired mobility and disability for the ageing populations. Therefore, due to the increasing prevalence of the malady, it is expected that clinical and scientific practices had to be set in order to detect the problem in its early stages. Thus, this work will be focused on the improvement of methodologies for problem solving aiming at the development of Artificial Intelligence based decision support system to detect knee osteoarthritis. The framework is built on top of a Logic Programming approach to Knowledge Representation and Reasoning, complemented with a Case Based approach to computing that caters for the handling of incomplete, unknown, or even self-contradictory information.